• DOMINANT TECHNOLOGIES IN “INDUSTRY 4.0”

    TESTING THE SYSTEMS OF THE AUTONOMOUS AGRICULTURAL ROBOT

    Industry 4.0, Vol. 3 (2018), Issue 3, pg(s) 134-137

    The aim of the paper was to test of the concept of the navigation system for the autonomous robot for sowing and wide row planting. Autonomous work of the robot in the field of traction and agronomic processes is implemented based on data from many sensors (cameras, position sensors, distance sensors, and others). The robot is intended for ecologic cultivation requiring mechanical removal of weeds or in crops with application of selective liquid agrochemicals limited to the minimum. The use of a vision system, based on the map coordinates of the position of the sown seeds, allows for their care on an early stage of plant development. Main sensor system is based on a specialized GPS receiver and inertial navigation providing position information with an accuracy of around 10 mm. To determine the angular acceleration the IMU (Inertial Measurement Unit) is used. Additionally, information from the acceleration sensors and wheel encoders is used for navigation purposes. This system is used to: control the speed of the robot, keep the robot on the designated path, and detect the precise position of the seeds. The exact information of the seeds position is used to build maps of seeds, which will be used as supporting information for precision weeding, and to control the position of and operation of key components. The front camera view is used to increase positioning accuracy of the robot. It will allow corrections of the robot path regarding the rows of plants. The vision system is also used for detection of non-moving objects. A structure of requirements for the SQL database has been developed, which is used to store plant and weed geo-data, as well as store data about plants and weeds, based on images recorded by the vision system.

  • ANALYSIS OF SYSTEM RELIABILITY BASED ON FAULT TOLERANT CONTROL AND USING VIBROACOUSTIC PARAMETER

    Mechanization in Agriculture, Vol. 62 (2016), Issue 3, pg(s) 7-9

    The paper presents possibility of fault detection and isolation in rotation machinery using analytical redundancy. It outlines the most important techniques of model-based residual generation using parameter identification and state estimation methods with emphasis the problems of reliability. A solution to the fundamental problem of fault detection providing the maximum achievable effectiveness by using condition-based maintenance system, reducing downtime, decreasing maintenance cost, and increasing machine availability is given. With the aim of synthesizing and providing the information of researcher`s community, this paper attempts to summarize and classify the recent published techniques in diagnosis and prognosis of rotating machinery. Furthermore, it also discusses the opportunities as well as the challenges for conducting advance research in the field of remain useful life prognosis.

    The results are very important for robust instrument fault detection, component fault detection and actuator fault detection. Finally we discuss the approach of fault diagnosis using a combination of analytical and knowledge-based redundancy.

  • CONCEPTION OF NAVIGATION SYSTEM FOR AUTONOMOUS AGRICULTURAL ROBOT

    Mechanization in Agriculture, Vol. 62 (2016), Issue 2, pg(s) 27-29

    The aim of the paper was to propose conception of the navigation system for the autonomous robot for sowing and wide row planting. Autonomous work of the robot in range of traction and agronomic processes will be implemented on the basis of data from a many sensors (cameras, sensors position, sensors distance, and others). Positive test results will allow for the use of the robot in organic crops requiring mechanical removal of weeds or in crops with application of selective liquid agrochemicals limited to the minimum The use of a vision system, based on the map coordinates of the position of the sown seeds , will allow for their care on an early stage of plant development. Main sensor system is based on a specialized GPS receiver providing position information with an accuracy of less than 100 mm. This system will be used to: control speed of the robot, guidance and maintenance robot on the designated path, precision seeding – the exact information on where sowing the seeds will be used to build maps of seeds, which will be used as supporting information for precision weeding, and to control the position of and operation of key components. The front camera view will be used to increase positioning accuracy of the robot. It will allow corrections of the robot path regarding the rows of plants. The vision system will also be used for detection of non-moving objects. Additionally information from the acceleration sensors and encoders built-in wheels will be used in navigation purposes. To determine the angular acceleration the IMU (Inertial Measurement Unit) will be required. During the preliminary phase of the project Authors are planning to test possibility of usage of several low cost sensors for collision avoidance system (moving objects detection).

  • USE OF FAULT TOLERANT CONTROL SYSTEMS IN AGRICULTURE MACHINERY

    Mechanization in Agriculture, Vol. 61 (2015), Issue 7, pg(s) 3-6

    The active fault-tolerant control approach relies heavily on the occurred faults. Higher performances and more rigorous security requirements have invoked an ever increasing demand to develop real time fault detection and isolation system. The problem of fault diagnosis using analytical redundancy (model-based) methods has received increasing attention during recent years due to the rapid growth in available computer power. The main objective is to design and maintenance a fault-tolerant control system which guarantees a high overall system reliability and dependability both in nominal operation and in the presence of faults. Such an objective is achieved by a control performance index, which is proposed based on system reliability analysis. The methods involve generation and evaluation of signals that are accentuated by faults that have actually occurred. The procedures for generating such signals, called residuals, are based on two main distinct approaches. Direct approach consists in the elimination of all the unknown variable , keeping input-output relations involving only observable variables. Indirect approach estimates states, outputs or parameters in order to generate discrepancy signals obtained by the difference between the actual variables and their estimates.